Manager, Data & Analytics

Saige Partners•Eden Prairie, MN

About The Position

We are seeking an experienced Data & Analytics Manager to lead analytics strategy, oversee key initiatives, and drive data-driven decision-making across the organization. This role leads an analytics team, manages reporting and analytics solutions, and expands the use of Business Intelligence (BI), Artificial Intelligence (AI), and Generative AI (GenAI) to improve business performance. The ideal candidate combines technical expertise, strategic leadership, and project management skills to deliver measurable business value.

Requirements

Bachelor’s degree in MIS, Data Science, Computer Science, Statistics, Analytics, or a related field.
8+ years of data and analytics experience, including at least 3 years in a leadership role.
Experience with enterprise AI tools, including Microsoft Copilot, Google Gemini, Claude, OpenAI, MCP, and A2A technologies.
Experience with databases, data warehouses, and data lakes.
Strong knowledge of BI tools such as Power BI, Tableau, or Looker.
Experience with cloud platforms, including Google Cloud Platform (GCP) and Microsoft Azure.
Experience delivering enterprise-level data science, AI, and GenAI solutions.
Strong project management, analytical, and problem-solving skills.
Proven ability to manage analytics portfolios and develop strategic roadmaps.
Excellent communication skills and the ability to influence stakeholders and senior leaders.

Responsibilities

Develop and prioritize analytics initiatives aligned with business goals.
Oversee the development of reports, dashboards, and analytics solutions.
Lead, coach, and develop analytics professionals.
Identify opportunities to use AI and GenAI to automate processes and improve decision-making.
Manage analytics projects and portfolios to ensure timely delivery and business alignment.
Collaborate with business leaders to translate needs into actionable data solutions.
Ensure analytics solutions are accurate, scalable, reliable, and user-friendly.
Track KPIs, solution adoption, and business impact.
Partner with data engineering, platform, integration, and governance teams.
Ensure data security and responsible AI practices while identifying opportunities to improve analytics capabilities.